Online review websites play an important role in customer’s purchase decision-making process for the useful product knowledge contained in the customer-generated reviews. However, the increasing information volume also makes it difficult for customers to identify and consider those attributes relevant to their decision. Based on Information Processing Theory (IPT) and Multiple Pathway Anchoring and Adjustment Model (MPAAM), we proposed three characteristics of online reviews affecting review helpfulness (e.g., attractiveness, representational sufficiency and functional sufficiency) and examined the moderating influences of information volume on these relationships. A large-scale review dataset from Yelp.com are collected and text analysis technique are applied to validate our research model. Our work, which illustrates the disturbance effect of information volume, has implications for both online word-of-mouth and information processing research.